Operational Optimization of Water Distribution Systems using a Hybrid Genetic Algorithm

Genetic algorithm (GA) optimization is well suited for optimizing the operation of water distribution systems, especially large and complex systems. GAs have good initial convergence characteristics, but slow down considerably once the region of optimal solution has been identified. In this study the efficiency of GA operational optimization was improved through a hybrid method which combines the GA method with a hillclimber search strategy. Hillclimber strategies complement GAs by being efficient in finding a local optimum. Two hillclimber strategies, the Hooke and Jeeves and Fibonacci methods, were investigated. The hybrid method proved to be superior to the pure GA in finding a good solution quickly, both when applied to a test problem and to a large existing water distribution system.

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